research DNN-DTIs: Improved Drug-Target Interactions Prediction Using XGBoost Feature Selection and Deep Neural Network
The DNN-DTIs method accurately predicts drug-target interactions and is useful for drug repositioning.
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research Prediction of Therapeutic Outcomes of Female Pattern Hair Loss Patients Based on Clinical Features with Application of Artificial Intelligence
Artificial intelligence can accurately predict hair growth and treatment results in female pattern hair loss patients, with age of onset and duration being key factors.
research Drug Repurposing Against KRAS Mutant G12C: A Machine Learning, Molecular Docking, and Molecular Dynamics Study
Afatinib, neratinib, and zanubrutinib could be effective against KRASG12C-mutant tumors.
research Androgen Signaling Regulates SARS-CoV-2 Receptor Levels and Is Associated with Severe COVID-19 Symptoms in Men
Male hormones affect COVID-19 severity and certain drugs targeting these hormones could help reduce the risk.
research A Machine Learning and Network Framework to Discover New Indications for Small Molecules
A machine learning model called CATNIP can predict new uses for existing drugs, like using antidepressants for Parkinson's disease and a thyroid cancer drug for diabetes.
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